Burned Area and Fire Severity Prediction of a Forest Fire Using a Sentinel 2-Derived Spectral Index in Çanakkale, Turkey

نویسندگان

چکیده

Objective: The objective of this study was to determine the extent and degree severity a burned area resulting from forest fire using Sentinel 2 remote sensing data in Çanakkale, Turkey within Mediterranean Basin, an world where occurrence are increasing. Materials Methods: Pre postfire images were obtained. Normalized Burn Ratio (NBR) index calculated for each scene. Then difference NBR (dNBR) by subtracting prefire NBR. dNBR ranges classified into categories. A map with 20 m spatial resolution displaying generated image. Finally, stand burn laid over examine relationship between cover types. Results: Approximately 1400 ha predicted have been burned. Twenty nine, 21, 42, 8% identified as low, moderate high, severely index, respectively. Conclusions: overlay on revealed that forested areas more compared agricultural sections. is effective delineate identify severity. provide fast accurate means monitor due its improved temporal resolution.

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ژورنال

عنوان ژورنال: Turkish journal of bioscience and collections

سال: 2022

ISSN: ['2602-4292']

DOI: https://doi.org/10.26650/tjbc.1082039